Using AI In Business Intelligence

Enterprise seems to be entering a new era ruled by data. What was once the realm of science fiction, AI in business intelligence is evolving into everyday business as we know it.

2016 was a great year for advancements in AI technologies and machine learning. The AI market is also flourishing. Despite all the hype and media attention, numerous startups and Internet giants are all racing to develop this technology. There have been massive increases in investment and adoptions of it by companies.

A study by Narrative Science found that last year alone 38% of businesses had already adopted AI. This uptake is expected to grow to 62% by 2018. Another study by Forrester Research predicts a 300% boom in investment in AI in 2017 compared to last year. The AI market is expected to grow to $47 billion by 2020 from $8 billion today.

Companies can now use machines algorithms to identify trends and insights in vast reams of data and make faster decisions that potentially position them to be competitive in real-time.

It’s not a simple process for companies to incorporate machine learning into their existing business intelligence systems, though Skymind CEO and past TechEmergence podcast guest Chris Nicholson advises that it doesn’t have to be daunting.“AI is just a box,” he says. “Math and code. If this, then that. That is the simplest way to describe it.” Organising data collection and testing an algorithm with this data for accuracy over the first few months is where many businesses get stuck.

But as AI has gained momentum, prominent application providers have gone beyond creating traditional software to developing more holistic platforms and solutions that better automate business intelligence and analytics processes. Major vendors, including General Electric, SAP, and Siemens, offer such software suites and operating systems, but there are a growing number of emerging providers in the market as well.

Natural language generation produces text from computer data. IT is currently used in customer services, report generation, summarising business intelligence insights and sales generation.

The tool takes advantage of natural language processing, an inference engine and natural language generation, fairly sophisticated AI technology, to undertake initial email contact with sales leads. Traditionally, CRM has been a place to build a record of customer interactions, but AI lets it be more than that. It’s about using the power of that platform to be a better salesperson, and giving them more time to spend working with customers and closing sales.

Based on our past interviews with executives and investors in the field, we predict that business intelligence applications will be one of the fastest growing areas for leveraging AI technology over the next five to 10 years.